为解决现有线性回归方法对市级卷烟销量预测研究效果不佳等问题,基于支持向量机(SVM,Support vector machine)设计并实现了一种市级卷烟销量预测方法.以湖南中烟工业有限责任公司卷烟销量为研究对象,将支持向量机(SVM)方法应用到卷烟销量预测中,提出了基于SVM的卷烟销量预测混合方法(SHPM,SVM-based hybrid prediction method).将SHPM与线性回归方法、ARIMA(Autoregressive integrated moving average)方法、SVM方法进行了市级卷烟销量预测的对比实验,结果表明:将SVM方法应用到卷烟销量预测中是可行的.在市级卷烟销量预测上,SHPM预测结果误差相比SVM方法降低9.58%,比线性回归方法降低11.83%,比ARIMA方法降低45.79%.因此,SHPM是一种有效的市级卷烟销量预测方法.%Not satisfied with the accuracy of cigarette sales volume prediction with linear regression method, an SHPM (SVM-based hybrid prediction method) was proposed based on SVM (Support vector machine) by taking the sales volume of China Tobacco Hunan Industrial Company Limited as objects. Municipal level cigarette sales volume predicted separately by SHPM, linear regression, ARIMA (autoregressive integrated moving average) and SVM were compared and analyzed. The results showed that it was feasible to predict cigarette sales volumes with SVM method. The prediction errors against SVM, linear regression and ARIMA reduced by 9.58%, 11.83% and 45.79%, respectively; SHPM prediction method was more effective.
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